One application of light transport simulation is the computational synthesis of images that cannot be distinguished from real photographs. In such simulation algorithms, light transport is modeled by a Fredholm integral equation of the second kind and pixel colors are determined by estimating functionals of the solution of the Fredholm integral equation. The estimators are averages of the contribution of sampled light transport paths or rays that connect light sources and camera sensors.
Compared to reality, where photons and trajectories are abundant, a computer may only consider a tiny fraction of path space, which is one of the dominant reasons that images have noise artifacts. Because the number of paths that may be traced is limited, increasing the number of light transport paths that have an important contribution to the image produces a higher quality image. While research in computer graphics has focused on importance sampling to increase the number of light transport paths that contribute to the image, for some time there has not been a simple and efficient online method that can substantially reduce the number of light transport paths having zero contribution to the image.
FIG. 1A illustrates a prior art diagram 100 of a light path. The surface is directly illuminated by the light source. As shown in FIG. 1A, multiple rays are scattered from a surface 102. When importance sampling is used, most of the rays are cast from the surface 102 in the direction of the light source. Radiance is integrated by sampling from a probability density function p that is proportional to the product of emitted radiance Le and the bidirectional scattering distribution function ƒr representing the physical surface properties. The fraction of radiance that is incident perpendicular to the surface, is taken into account by the cosine of the angle θ between the surface normal and the direction of incidence.
FIG. 1B illustrates a prior art diagram 110 of an occluded light transport path. The surface 102 should be indirectly illuminated by the light source because the object 105 occludes the light path. Importance sampling does not consider occluding objects, so all of the rays fail to reach the light source. Light transport paths with zero contribution to the image cannot be avoided unless visibility is considered. For example, when a portion of a scene is lit by a light behind a door and the door position changes from open to nearly closed, the occlusion problem can be made arbitrarily more difficult to solve. There is a need for addressing these issues and/or other issues associated with the prior art.